What are limitations validation set of approach over k-fold cross validation?

@harry wrote:

I am currently studying about the methods by which I can estimate the test error while building the model on training data.While studying I came across two methods first is validation approach and other is k-fold cross validation approach.

Validation approach- In this we randomly divide the given data set of samples into two parts
1) training set
2) validation set

k-fold cross validation- In this we randomly divide the data into K equal-sized parts. We leave out part k, fit the model to the other K - 1 parts (combined), and then obtain predictions for the left-out kth part.

I want to know the limitations of validation approach over k-fold cross validation approach.

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